Cargando…

Statistical inference based on divergence measures

The idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete m...

Descripción completa

Detalles Bibliográficos
Autor principal: Pardo, Leandro
Lenguaje:eng
Publicado: Taylor and Francis 2005
Materias:
Acceso en línea:http://cds.cern.ch/record/1991428
_version_ 1780945770710564864
author Pardo, Leandro
author_facet Pardo, Leandro
author_sort Pardo, Leandro
collection CERN
description The idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete models, many statisticians remain unaware of this powerful approach.Statistical Inference Based on Divergence Measures explores classical problems of statistical inference, such as estimation and hypothesis testing, on the basis of measures of entropy and divergence. The first two chapters form an overview, from a statistical perspective, of the most important measures of entropy and divergence and study their properties. The author then examines the statistical analysis of discrete multivariate data with emphasis is on problems in contingency tables and loglinear models using phi-divergence test statistics as well as minimum phi-divergence estimators. The final chapter looks at testing in general populations, presenting the interesting possibility of introducing alternative test statistics to classical ones like Wald, Rao, and likelihood ratio. Each chapter concludes with exercises that clarify the theoretical results and present additional results that complement the main discussions.Clear, comprehensive, and logically developed, this book offers a unique opportunity to gain not only a new perspective on some standard statistics problems, but the tools to put it into practice.
id cern-1991428
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2005
publisher Taylor and Francis
record_format invenio
spelling cern-19914282021-04-21T20:28:31Zhttp://cds.cern.ch/record/1991428engPardo, LeandroStatistical inference based on divergence measuresMathematical Physics and MathematicsThe idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete models, many statisticians remain unaware of this powerful approach.Statistical Inference Based on Divergence Measures explores classical problems of statistical inference, such as estimation and hypothesis testing, on the basis of measures of entropy and divergence. The first two chapters form an overview, from a statistical perspective, of the most important measures of entropy and divergence and study their properties. The author then examines the statistical analysis of discrete multivariate data with emphasis is on problems in contingency tables and loglinear models using phi-divergence test statistics as well as minimum phi-divergence estimators. The final chapter looks at testing in general populations, presenting the interesting possibility of introducing alternative test statistics to classical ones like Wald, Rao, and likelihood ratio. Each chapter concludes with exercises that clarify the theoretical results and present additional results that complement the main discussions.Clear, comprehensive, and logically developed, this book offers a unique opportunity to gain not only a new perspective on some standard statistics problems, but the tools to put it into practice.Taylor and Francisoai:cds.cern.ch:19914282005
spellingShingle Mathematical Physics and Mathematics
Pardo, Leandro
Statistical inference based on divergence measures
title Statistical inference based on divergence measures
title_full Statistical inference based on divergence measures
title_fullStr Statistical inference based on divergence measures
title_full_unstemmed Statistical inference based on divergence measures
title_short Statistical inference based on divergence measures
title_sort statistical inference based on divergence measures
topic Mathematical Physics and Mathematics
url http://cds.cern.ch/record/1991428
work_keys_str_mv AT pardoleandro statisticalinferencebasedondivergencemeasures